Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Edoardo Vecchi"'
Autor:
Illia Horenko, Lukáš Pospíšil, Edoardo Vecchi, Steffen Albrecht, Alexander Gerber, Beate Rehbock, Albrecht Stroh, Susanne Gerber
Publikováno v:
Journal of Imaging, Vol 8, Iss 6, p 156 (2022)
We propose a pipeline for synthetic generation of personalized Computer Tomography (CT) images, with a radiation exposure evaluation and a lifetime attributable risk (LAR) assessment. We perform a patient-specific performance evaluation for a broad r
Externí odkaz:
https://doaj.org/article/a5d4a186d82d48bf86372e4930ed3b04
Autor:
Steffen Albrecht, Jens R. Vandevelde, Edoardo Vecchi, Gabriele Berra, Davide Bassetti, Maik C. Stüttgen, Heiko J. Luhmann, Illia Horenko
With the help of high-performance computing, we benchmarked a selection of machine learning classification algorithms on the tasks of whisker stimulus detection, stimulus classification and behavior prediction based on electrophysiological recordings
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dfd4fa0efe9501a09d841ebc1e4529b1
https://doi.org/10.1101/2023.04.19.537473
https://doi.org/10.1101/2023.04.19.537473
Autor:
Illia Horenko, Edoardo Vecchi, Juraj Kardoš, Andreas Wächter, Olaf Schenk, Terence J. O’Kane, Patrick Gagliardini, Susanne Gerber
Publikováno v:
Proceedings of the National Academy of Sciences. 120
Regression learning is one of the long-standing problems in statistics, machine learning, and deep learning (DL). We show that writing this problem as a probabilistic expectation over (unknown) feature probabilities – thus increasing the number of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::742b3d5ef06ccb71770de4a8d75be83b
https://doi.org/10.1073/pnas.2214972120
https://doi.org/10.1073/pnas.2214972120
Publikováno v:
Research in International Business and Finance. 65:101958
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f318fe77578cbb629c4cc390afe40d6
https://doi.org/10.1016/j.ribaf.2023.101958
https://doi.org/10.1016/j.ribaf.2023.101958
Publikováno v:
Neural computation. 34(5)
Classification problems in the small data regime (with small data statistic T and relatively large feature space dimension D) impose challenges for the common machine learning (ML) and deep learning (DL) tools. The standard learning methods from thes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1cd9e25aa670d4663bfd350dd250fc61
https://pubmed.ncbi.nlm.nih.gov/35344997
https://pubmed.ncbi.nlm.nih.gov/35344997
Autor:
Steffen Albrecht, Albrecht Stroh, Edoardo Vecchi, Alexander Gerber, Illia Horenko, Susanne Gerber, Beate Rehbock, Lukáš Pospíšil
We propose a pipeline for a synthetic generation of personalized Computer Tomography (CT) images, with a radiation exposure evaluation and a lifetime attributable risk (LAR) assessment. We perform a patient-specific performance evaluation for a broad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::45d59da928066f3611b74b27e6591507
https://doi.org/10.1101/2021.08.10.455778
https://doi.org/10.1101/2021.08.10.455778
Autor:
Antonio Piralla, Matteo Ricchi, Maria Grazia Cusi, Paola Prati, Nadia Vicari, Giada Scarsi, Claudia Gandolfo, Gabriele Anichini, Chiara Terrosi, Elena Percivalle, Edoardo Vecchio Nepita, Federica Bergami, Monica Tallarita, Raffaella Di Martino, Alessandro Ferrari, Francesca Rovida, Giovanna Lunghi, Roberta Schiavo, Fausto Baldanti
Publikováno v:
International Journal of Infectious Diseases, Vol 102, Iss , Pp 299-302 (2021)
Real-time reverse transcription PCR is currently the most sensitive method to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Defining whether a patient could be contagious or not contagious in the presence of residual SARS-CoV-2
Externí odkaz:
https://doaj.org/article/8db9e3c000804b30a2f3ea82bc69eb4e
Publikováno v:
Open Ceramics, Vol 1, Iss , Pp 100006- (2020)
During the current pandemic of COVID-19 caused by the new Coronavirus SARS-CoV-2, the confinement measures slowed down the contagion, but did not completely avoid the disease diffusion for health workers, patients and the remaining population. The in
Externí odkaz:
https://doaj.org/article/e34f46b9a1fa4a3aad53d34532eb5070
Autor:
Manuela Donati, Andrea Balboni, Karine Laroucau, Rachid Aaziz, Fabien Vorimore, Nicole Borel, Federico Morandi, Edoardo Vecchio Nepita, Antonietta Di Francesco
Publikováno v:
PLoS ONE, Vol 11, Iss 2, p e0149914 (2016)
The aims of the present study were to assess the prevalence of Chlamydia suis in an Italian pig herd, determine the tetracycline susceptibility of C. suis isolates, and evaluate tet(C) and tetR(C) gene expression. Conjunctival swabs from 20 pigs were
Externí odkaz:
https://doaj.org/article/d977341b7d154adcb01410dfeb05f2ae